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Imaging of Micromotion Targets With Rotating Parts Based on Empirical-Mode Decomposition

机译:基于经验模态分解的旋转零件微运动目标成像

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For micromotion targets with rotating parts, the inverse synthetic-aperture-radar image of the main body may be shadowed by the micro-Doppler. To solve this problem, this paper proposes an imaging algorithm based on the complex-valued empirical-mode decomposition. First, the radar echoes are decomposed into a series of complex-valued intrinsic-mode functions (IMFs). Then, the IMFs from the rotating parts and those from the main body are separated according to the characteristics of their zero-crossings. Finally, the well-focused imaging of the main body via traditional imaging algorithm and the accurate parameter estimation of the rotating part can be obtained. Both the imaging results for the simulated and measured data are given to verify the validity of the proposed algorithm.
机译:对于带有旋转部件的微动目标,微多普勒可能会掩盖主体的逆合成孔径雷达图像。为了解决这个问题,本文提出了一种基于复值经验模态分解的成像算法。首先,将雷达回波分解为一系列复数值本征模式函数(IMF)。然后,根据旋转部分的零交叉特性将来自旋转部分的IMF和来自主体的IMF分离。最后,通过传统的成像算法对主体进行了良好的聚焦成像,并对旋转部件的参数进行了精确估计。给出了模拟数据和测量数据的成像结果,以验证所提出算法的有效性。

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